Principles for Accountable Algorithms en Social Impact Statement for Algorithms
This FAT / ML tool (or in full "Fairness, Accountability and Transparency in Machine Learning") aims to promote the following ethical principles:
- responsibility
- explainability
- accuracy
- controllability
- honesty
To clarify exactly what is meant, the makers of FAT / ML have formulated clear questions and defined focus points to monitor and promote these principles.
FAT / ML is an annual conference aimed at connecting researchers and discussing how to identify and solve problems of computationally rigorous methods.
What you should know before reading further:
- Target group: developers and product managers
- Process phase: design, implementation
- System component: data usage and processing, users, context of AI system
- Price indication: freely available
Method
The tool consists of a number of questions that help you to ensure the above principles. The tool also includes steps you can take to further explore these principles in your AI project. It is an iterative process. This means that this exercise takes place 3 times, namely:
- during design
- before deployment
- upon deployment
Result
The result is a Social Impact Statement of Algorithms. You can make this statement available as a developer or provider when the product is launched. By using this method it becomes possible to judge how an algorithm can affect society.
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Link
Go to the tool
https://www.fatml.org/resources/principles-for-accountable-algorithmsThis tool was not developed by the Knowledge Center Data & Society. We describe the tool on our website because it can help you deal with ethical, legal or social aspects of AI applications. The Knowledge Center is not responsible for the quality of the tool.